Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "77"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 77 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 50 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 48 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 77, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459865 not_connected 100.00% 0.00% 0.00% 0.00% - - 40.216850 42.852898 25.966523 20.685443 7.148437 13.002825 18.007204 9.526709 0.6050 0.5363 0.2017 nan nan
2459864 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459863 not_connected 100.00% 0.00% 0.00% 0.00% - - 30.546287 32.371554 0.560536 -0.516649 1.386381 3.603793 11.904003 3.144543 0.5684 0.4945 0.2166 nan nan
2459862 not_connected 100.00% 0.00% 0.00% 0.00% - - 33.202397 35.854876 16.243449 12.721044 5.655920 11.614850 5.632853 2.846572 0.5456 0.5389 0.2251 nan nan
2459861 not_connected 100.00% 0.00% 0.00% 0.00% - - 21.026536 24.543967 -0.413833 -1.566538 2.476946 0.501349 17.323525 2.594812 0.5959 0.5240 0.2652 nan nan
2459860 not_connected 100.00% 0.00% 0.00% 0.00% - - 23.365500 25.547129 12.744943 9.772867 6.656115 12.610665 4.671543 1.534635 0.5960 0.5168 0.2521 nan nan
2459859 not_connected 100.00% 0.00% 0.00% 0.00% - - 17.699544 19.019436 -0.208274 -1.418830 0.306597 -0.066606 3.343778 1.954431 0.5980 0.5329 0.2417 nan nan
2459858 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 18.127431 20.234170 -0.602161 -1.804118 0.697327 0.031500 13.060809 7.469874 0.6156 0.5426 0.2667 2.870308 2.249178
2459857 not_connected 0.00% 100.00% 100.00% 0.00% - - 1.437309 0.540482 2.413569 3.709776 -0.476360 0.155402 -0.263113 -1.231451 0.0299 0.0297 0.0006 nan nan
2459856 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 28.492104 29.798028 12.122770 9.833387 3.052085 6.969325 3.097286 1.483104 0.5926 0.5552 0.2451 3.534344 2.705734
2459855 not_connected 100.00% 0.77% 0.00% 0.00% 100.00% 0.00% 35.533569 34.843190 13.321055 11.261713 1.146479 2.941226 6.470647 14.007814 0.5591 0.5743 0.2685 2.961751 2.334002
2459854 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 35.885481 38.274851 11.523629 9.544801 1.658963 1.922376 3.645412 -0.608629 0.5956 0.5937 0.2398 2.743506 2.279974
2459853 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 292.259756 292.608523 inf inf 4728.737953 4631.840688 12068.621199 11528.598379 nan nan nan 0.000000 0.000000
2459852 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.715114 11.382575 14.904098 11.205798 6.057982 9.532884 12.251533 10.478424 0.7479 0.7374 0.1719 7.983626 6.718125
2459851 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 19.530516 29.210251 16.962232 12.716167 12.404738 26.086355 11.659870 10.393128 0.6462 0.6123 0.2045 3.790983 2.635760
2459850 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 25.352745 31.082167 14.244626 11.176956 7.059678 13.033647 7.999199 7.354579 0.6247 0.6201 0.1902 2.913957 2.260792
2459849 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 25.549933 30.106786 29.009186 23.771947 5.758002 8.348602 5.513717 2.670629 0.6245 0.6116 0.2090 3.435027 2.606431
2459848 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 23.479580 25.509194 20.777376 16.839054 10.933478 16.138107 5.967269 0.755046 0.6119 0.6276 0.2091 4.205692 3.083327
2459847 not_connected 100.00% 0.00% 6.44% 0.00% 100.00% 0.00% 28.014516 33.511655 19.403641 15.257380 12.893596 13.686189 33.369907 3.165302 0.6173 0.5238 0.2964 3.273035 2.324259
2459846 not_connected 100.00% 0.00% 42.74% 0.00% 100.00% 0.00% 23.991533 26.858230 14.175578 11.046340 14.393575 14.793259 7.921027 1.799559 0.7603 0.5376 0.3751 4.573973 2.692753
2459845 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 30.499633 33.095393 26.231513 22.260447 6.510995 11.050399 8.830239 6.261732 0.6329 0.6267 0.2081 0.000000 0.000000
2459844 not_connected 100.00% 100.00% 100.00% 0.00% - - 5.379697 2.628111 64.017585 70.303799 323.101396 322.764064 222.771750 215.206696 0.0292 0.0297 0.0005 nan nan
2459843 not_connected 100.00% 1.20% 0.66% 0.00% 100.00% 0.00% 13.188014 15.997729 18.084359 16.637240 5.429292 9.566976 5.666674 2.454352 0.6213 0.6149 0.2088 0.000000 0.000000
2459842 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 5.251996 7.179948 -0.241189 -1.355303 -1.106839 -0.710425 -0.446842 -0.633548 0.6450 0.5008 0.1946 5.054787 5.305572
2459841 not_connected 100.00% 100.00% 100.00% 0.00% - - 43.082983 25.294625 56.314161 55.986203 26.622803 22.587564 18.643644 8.649848 0.0302 0.0307 0.0013 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 77: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 42.852898 40.216850 42.852898 25.966523 20.685443 7.148437 13.002825 18.007204 9.526709

Antenna 77: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape nan nan nan inf inf nan nan nan nan

Antenna 77: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 32.371554 30.546287 32.371554 0.560536 -0.516649 1.386381 3.603793 11.904003 3.144543

Antenna 77: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 35.854876 33.202397 35.854876 16.243449 12.721044 5.655920 11.614850 5.632853 2.846572

Antenna 77: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 24.543967 24.543967 21.026536 -1.566538 -0.413833 0.501349 2.476946 2.594812 17.323525

Antenna 77: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 25.547129 23.365500 25.547129 12.744943 9.772867 6.656115 12.610665 4.671543 1.534635

Antenna 77: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 19.019436 17.699544 19.019436 -0.208274 -1.418830 0.306597 -0.066606 3.343778 1.954431

Antenna 77: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 20.234170 20.234170 18.127431 -1.804118 -0.602161 0.031500 0.697327 7.469874 13.060809

Antenna 77: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Power 3.709776 0.540482 1.437309 3.709776 2.413569 0.155402 -0.476360 -1.231451 -0.263113

Antenna 77: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 29.798028 28.492104 29.798028 12.122770 9.833387 3.052085 6.969325 3.097286 1.483104

Antenna 77: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected ee Shape 35.533569 34.843190 35.533569 11.261713 13.321055 2.941226 1.146479 14.007814 6.470647

Antenna 77: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 38.274851 38.274851 35.885481 9.544801 11.523629 1.922376 1.658963 -0.608629 3.645412

Antenna 77: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Power inf 292.608523 292.259756 inf inf 4631.840688 4728.737953 11528.598379 12068.621199

Antenna 77: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected ee Power 14.904098 7.715114 11.382575 14.904098 11.205798 6.057982 9.532884 12.251533 10.478424

Antenna 77: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 29.210251 19.530516 29.210251 16.962232 12.716167 12.404738 26.086355 11.659870 10.393128

Antenna 77: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 31.082167 25.352745 31.082167 14.244626 11.176956 7.059678 13.033647 7.999199 7.354579

Antenna 77: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 30.106786 25.549933 30.106786 29.009186 23.771947 5.758002 8.348602 5.513717 2.670629

Antenna 77: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 25.509194 25.509194 23.479580 16.839054 20.777376 16.138107 10.933478 0.755046 5.967269

Antenna 77: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 33.511655 33.511655 28.014516 15.257380 19.403641 13.686189 12.893596 3.165302 33.369907

Antenna 77: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 26.858230 23.991533 26.858230 14.175578 11.046340 14.393575 14.793259 7.921027 1.799559

Antenna 77: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 33.095393 33.095393 30.499633 22.260447 26.231513 11.050399 6.510995 6.261732 8.830239

Antenna 77: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected ee Temporal Variability 323.101396 5.379697 2.628111 64.017585 70.303799 323.101396 322.764064 222.771750 215.206696

Antenna 77: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
77 N06 not_connected ee Power 18.084359 15.997729 13.188014 16.637240 18.084359 9.566976 5.429292 2.454352 5.666674

Antenna 77: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected nn Shape 7.179948 5.251996 7.179948 -0.241189 -1.355303 -1.106839 -0.710425 -0.446842 -0.633548

Antenna 77: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
77 N06 not_connected ee Power 56.314161 43.082983 25.294625 56.314161 55.986203 26.622803 22.587564 18.643644 8.649848